Home » Clinical Scenario – JIA

Chiara and Simona are affected by Juvenile Idiopathic Arthritis (JIA). Their age at disease onset was 4 years old and they both tested positive for antinuclear antibodies. They both had an asymmetric involvement of knee and ankle at disease onset. Within 1 year both Chiara and Simona showed wrist involvement and started a treat-ment with second line agent. Chiara experienced a severe and irreversible structural damage progression, as revealed by a 4-year follow-up radiography.

Simona developed a milder course of the disease and her 4-year follow-up radiography showed no significant signs of structural damage. Notably, at disease onset demographic, routine clinical and laboratory data did not significantly differ be-tween these two girls. It was not possible, therefore, us-ing traditional methods to distinguish which of them would develop a more aggressive disease.

Using MD-Paedigree to set their data in a multi-scale inte-grated model clinical, immunological and meta-genetic data, as well as biomechanical analysis results, outcome predictors are identified. This means that Chiara’s more severe course of the disease is determined and her need for earlier treatment is established.

A comprehensive model of JIA-related changes in two joints (wrist and ankle) is available. Different imaging modalities (i.e., MRI) provide information to classify the degree of bone erosion and synovitis in both regions. For this, automated image analysis tools are developed to reduce the time necessary for performing that task and becoming independent from the individual observer.

En-hanced biomechanical models are generated by adapting highly sophisticated standard models to the individual case and thus predicting locomotive changes caused by JIA. These are tested against results of a personalised gait analysis that enriches this model by providing more details about the locomotive constraints for the considered joints.

The MD-Paedigree database contains morphological changes visible in the image data and clinical, immunological, genetic and metagenetic data. Having access to such a large classified individual JIA cases repository helps to better predict the girls’ disease progression and provide them with medication that is specifically adapted to them.

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